Women in STEM

Heidi Blackburn & Jason Heppler

3/28/2019

The following notebook analyzes gender in STEM publications. The content was developed by Heidi Blackburn and Jason Heppler, University of Nebraska at Omaha. Last updated **April 19, 2019*.

Data analytics

Count of authors by gender.

Top publications by number of articles.

Top conference publications by number of article.

Top publications (including journals and conference proceedings.)

Number of publications by year.

Total number of articles.

Data plots

The top publications per year.

The number of articles per publication.

Authorship by position.

Stacked barchart of gender by year.

Gender by journal vs. conference.

Counting the number of authors by position.

Network analysis

We want to look at two networks:

  1. Where do people publish most often (bimodal)
  2. Who publishes with each other

Graph of authors and publications bimodal network, colored by author and publication.

Graph of authors and their co-authors, colored by gender. (NB: This isn’t working yet.)

Summary statistics

Number of journals that accounted for % of references.

Number of journals.

Number of conference proceedings.

Top three journal publications and their counts. ASEE at 32, Sex Roles at 21, and Journal of Women and Minorities in Science and Engineering at 21.

Top twenty journals that publish articles on women in STEM in higher education.

Number of authors and their count of articles.

Number of authors that published n% of the works.

Percentage of authors that write with a co-author.

TODO: code to write

Number of publishers and percentage of journals they own.

Top publisher with top three journal titles

NB: The trick here is that there are ties in the dataset, and my code doesn’t account for those ties (it was pretty tricky to get this working). If necessary, I might be able to modify this to try and show all cases where there are ties. Sort by publisher to see the top publishers and their corresponding top three journal titles.

Percentage increase in journals published between 2007 and 2018.

Total percentage increase between 2007 and 2018 across proceedings and journals.

perc_increase_low <- data %>% filter(date == 2007) %>% count()
perc_increase_high <- data %>% filter(date == 2018) %>% count()
  
paste0(round(perc_increase_high/ perc_increase_low * 100, 2), "%")
## [1] "2420%"

Percentage increase in journal articles from top publishing journals.

Percentage increase in conference proceeding publications.

Percentage of studies published outside traditional STEM journals.